Alexander D'Amour

Evaluating how biases in language models affect real-world applications.

Learn how to adapt models for different data sets effectively.

Data balancing is crucial for fairness and accuracy in machine learning models.

Exploring fairness issues in AI language models and their implications.

Understanding the pitfalls of reward hacking in AI systems and its implications.